feat: add centralized input validation for forecasters - #10
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Adds Forecaster.validate_input to catch missing columns, empty DataFrames, and non-positive horizons before model inference. Also rejects FoundationForecast(models=[]) at construction time. Closes #7.
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Closes #7.\n\nAdds
Forecaster.validate_inputto check required columns, non-empty DataFrames, and positive horizons before any model is loaded or API called. Validation is applied inForecaster.cross_validationandMultiModelForecasterMixin._call_models, so both single-model and multi-model entry points fail early with consistent error messages.\n\nAlso rejectsFoundationForecast(models=[])during construction instead of waiting for a forecasting method.